All Questions
16,348 questions
2
votes
1
answer
676
views
Does DTW return smaller distance measure than Euclidean Distance?
QUESTION 1: When computing the distance between two time series, shouldn't the DTW distance measure return a smaller distance than the Euclidean distance (assuming DTW internally uses the Euclidean ...
CommunityBot
- 1
5
votes
2
answers
1k
views
Similarity between time series signals
Lets say I have 2 time series that look like this for a number of different test subjects:
The lines represent values on 2 different metrics recorded at different points in time (minutes)
I have a ...
CommunityBot
- 1
1
vote
0
answers
50
views
Opposite results using Bayesian (STAN) vs Multilevel model (nlme). How is this possible?
My datasets contains the median wages and the cumulative installed wind-capacity for 4000 counties over a period of 20 years. The wages tend to rise over the period and the capacity tends to highly ...
- 82.8k
0
votes
1
answer
882
views
Comparing top level group effects using a 3-level hierarchical regression
I would like to detect group effects (if any) along with statistical confidences. I have a hierarchical data set structured as follows:
Drug Groups
...
CommunityBot
- 1
1
vote
2
answers
362
views
How to apply PCA results on a Future Dataset?
I have a fundamental question regarding the applications of the results of PCA:
If we have already performed a successful PCA on a dataset of, say, real estate prices of a certain region over the last ...
CommunityBot
- 1
7
votes
0
answers
74
views
+50
Why don't we typically worry about stationarity in panel data models with fixed effects?
Why don't we typically worry about stationarity in panel data models with fixed effects?
In time series analysis, stationarity is often a crucial assumption. However, I've noticed that in applied ...
- 1
1
vote
1
answer
296
views
Clusters as input for classification
I'm currently performing clustering as a batch job and then in real time I'm assigning new points to cluster whose centroid is closest to new arrived point.
The other approach that I see is to ...
CommunityBot
- 1
0
votes
1
answer
32
views
Fitting a Nonlinear Mixed Model
I’m trying to fit a nonLinear Mixed Model (nLMM) to test whether the abundance of certain organisms was affected by the sampling period after an event that caused a significant increase.
The data show ...
- 473
0
votes
1
answer
1k
views
Identifying positive and negative shocks in impulse responses
Dear StackExchange community,
I'd have a question on impulse responses that I have not found an answer to in econometrics textbooks. Specifically, I would want to know how to interpret impulse ...
CommunityBot
- 1
2
votes
2
answers
2k
views
Regression with multiple variables and time series (in SPSS)
I tried to find similar questions on this topic but couldn't find anything that helped me with my problem, so I will try to explain it on my own.
I'm trying to do a regression analysis on revenue for ...
CommunityBot
- 1
0
votes
1
answer
948
views
Determining order of ARIMA(p,d,q) from ACF and PACF
I know that when trying to determine if you have an AR(p) or MA(q) process, you look at the PACF and if it drops off significantly at a lag p, then you can say it's an AR(p), but if it's geometrically ...
CommunityBot
- 1
0
votes
1
answer
389
views
Moving average filter for estimating the seasonal component
I am reading the Introduction to Time Series and Forecasting Peter J. Brockwell • Richard A. Davis (Third Edition). I am having problems for understanding the estimation of seasonal component using ...
CommunityBot
- 1
2
votes
2
answers
1k
views
Rolling Window Forecasting with ARIMAX while supplying actual values
I am comparing different exogenous variables in how good they support the forecast of the monthly seasonal adjusted unemployment rate. All my data is monthly (2006-01-01 until 2018-09-01) and ...
CommunityBot
- 1
1
vote
2
answers
30
views
Should I conduct a multilevel for this or another analysis? Need help
I have three sources of data (teachers, parents and students) assessing students, in three waves. I want to assess all and see the differences between moments but then I also want to use variables for ...
- 809
2
votes
2
answers
2k
views
SARIMAX: transforming the exogenous variables
I am trying to build a (S)ARIMAX model where the endogenous variable (daily stock log-returns) has already been transformed: the log returns are the first difference of the logs of the daily stock ...
CommunityBot
- 1
1
vote
0
answers
34
views
Preprocessing and model selection strategies
I am working on a fault detection problem where each sample is a time series labeled with a specific type of fault. I am using a CNN model and a validation set for hyperparameter tuning. Currently, I ...
- 77
2
votes
1
answer
42
views
Why can't a non-stationary AR process be represented as an infinite MA process? [duplicate]
Consider the AR(1) process. If $|\phi|<1$, the process is stationary, and we can express the series as
$$ Y_t = \epsilon_t + \phi\epsilon_{t-1} + \phi^2\epsilon_{t-2} + \phi^3\epsilon_{t-3} + \...
- 2,875
4
votes
1
answer
3k
views
Adding noise to time series data to increase training data
I am dealing with a weekly time series forecasting problem and I am currently investigating the use of an LSTM to make a multi-step forecast for a univariate time series. I actually have a ...
CommunityBot
- 1
1
vote
1
answer
30
views
Identifying Poorly Forecastable Time Series Using tsfeatures
I am working on a problem involving the identification of poorly forecastable time series using features extracted with the tsfeatures library by Rob J. Hyndman. Below are the key details about my ...
- 131k
0
votes
0
answers
21
views
Clarifications on Hurst Exponent Definitions and Persistence Properties
I have a question regarding the Hurst exponent that I hope someone here can help clarify.
It is well known that there are different definitions of the Hurst exponent, but finding clear connections or ...
- 1
0
votes
1
answer
36
views
Best parameter of exponential smoothing when applied on a random walk
Let's say I have a random walk:
$$X_t = X_0 + \sum_{i =1}^t \epsilon_i$$
with the $\epsilon_i \sim \mathcal{N}(0, \sigma^2)$ and independent.
Then what smoothing factor $\alpha$ in an exponential ...
- 69.5k
2
votes
2
answers
962
views
Scaling unknown time series for prediction with RNN
I'm trying to build a RNN model to predict arterial blood pressure (ABP) time series based on two other time series, namely, ECG and PPG.
It is available to me a set of multivariate time series of ...
CommunityBot
- 1
1
vote
0
answers
20
views
Regression models that depend on outputs of other regression models
There is a milk factory with the following variables available at the weekly level (i.e. data at the end of each week) and orders are finished on a first in first out basis:
total incoming orders (...
- 141
2
votes
1
answer
630
views
Generalized Hurst Exponent - What value to specify for $\tau_{\max}$?
Consider a time series $X: S \to \mathbb{R}$, where $S := \{\nu, 2\nu, 3\nu, \ldots T\}$, and $T$ is a multiple of $\nu > 0$. For each $\tau \in (0, \tau_{\max}] \cap S$ and $q \in \mathbb{N}$, ...
- 82.8k
2
votes
0
answers
340
views
Assumptions for Hurst exponent calculation
Are there any general assumptions for the calculation of the Hurst exponent?
Does the signal need to be stationary, for example?
Does it depend on the method?
What about the length of the time ...
- 82.8k
-1
votes
1
answer
2k
views
Time-series modeling on a panel dataset
I have been trying to do some predictive modeling using models such as ARMA on a panel data set in python. The dependent variable in my problem is sales, and I have the sales time series of different ...
CommunityBot
- 1
2
votes
2
answers
2k
views
How can I determine how often an event occurs based on collected data how long one has to wait for an occurence
This is an experiment I can only observe, not design/change.
I make the following observations: A police officer frequently monitors the same traffic location in the same manner. I see the officer ...
CommunityBot
- 1
0
votes
1
answer
2k
views
K in Fourier series - How to find value of K to use it in ARIMA?
I am using the forecast library for doing some time series forecasting. I need to forecast number of sold items. I am planning to add holidays as xreg in auto.arima. The holiday will be a 0/1 list, ...
CommunityBot
- 1
1
vote
1
answer
478
views
Correlation of time-series at specific timestamp
Suppose, I have several hundred time series that are originating from one system and probably correlate. Now suppose, one of the signals, lets say signal A, shows strange behavior at several ...
CommunityBot
- 1
0
votes
0
answers
14
views
Determining how much timeseries relationships are driven by periodicity versus date relationships?
Given three timeseries of monthly data all ending at 11/30/2024 (A beginning at 12/31/2023, B beginning at 3/31/2024, and C beginning at 9/30/2024), one could present the timeseries as 1) aligned on ...
1
vote
1
answer
27
views
Stationarity Conditions VECM
Suppose we have a vector error correction model (VECM)
$$
\Delta y_{t}=\Pi y_{t-1}+\Gamma_{1}\Delta y_{t-1}+\cdot\cdot\cdot+\Gamma_{p-1}\Delta y_{t-p+1}+u_{t}
$$
A simple way to confirm that it is a ...
- 2,297
0
votes
0
answers
16
views
How to aggregate daily sales data to weekly for thousands of products? [closed]
I have a dataset with daily sales and prices of three thousand products for 5 years and three stores. I want to visualize price and sales trends during weeks of a year. I was thinking of creating a ...
2
votes
1
answer
267
views
Which steps have to be done before fitting logistic curve to time-series?
I want to cluster time-series concerning sales of products. In the database I have 26weeks after launching each products and units sold each week.
One of the method of clustering is to cluster ...
CommunityBot
- 1
0
votes
1
answer
7k
views
How to design a many-to-many LSTM RNN in Keras
I have timeseries data with 1 minute cadence with 4 features, and I want to try to predict the time-evolution of 2 of these features using a RNN using LSTMs in Keras. My aim is to predict the e.g. ...
CommunityBot
- 1
0
votes
0
answers
24
views
Difficulty in Deriving a Estimator Using Survey Means from Individual Forecasts
I would like to clarify a doubt regarding the paper Testing the Rationality of Price Forecasts: New Evidence from Panel Data (by MICHAEL P. KEANE AND DAVID E. RUNKLE) that presents an estimator ...
- 121
1
vote
1
answer
2k
views
Interpreting ARIMA prediction results
I have used an ARIMA(1,1,0) model on a stationary time series.
The time series shows amount of fires (number between 0 and 12) per day over a few years in regions of Moscow.
Both fitted and predicted ...
CommunityBot
- 1
0
votes
0
answers
18
views
How to Forecast Sales for Sub-Locations Without Historical Proportion Data?
I have a time series dataset of total sales for a product in a store over time. This product is available in two different locations within the store: one stand near the checkout and another stand in ...
- 82.8k
3
votes
3
answers
583
views
How to make two perfectly negatively correlated growing Geometric Brownian Motion (GBM) series? (Impossibility)
Intro
I am self studying in Youtube the course MIT 18.S096 Topics in Mathematics w Applications in Finances and in the following lecture min 34:50 by Dr. Jake Xia is studied the efficient frontier of ...
- 19.5k
3
votes
1
answer
46
views
Calculate marginal effects for random effects model with two crossed random effects
I am trying to get effects marginal of two crossed random effects (using STAN or brms). I understand how to do it for a single random effect following McElreath's book and Kurtz's brms version of the ...
- 10.7k
2
votes
1
answer
396
views
Difference between cross validation vs model accuracy measures
I have a time series ARIMA model and I want to validate the accuracy my prediction. But I dont understand the difference of using cross validation vs model accuracy measures such as MAPE, MAE, MSE and ...
CommunityBot
- 1
0
votes
1
answer
592
views
Trend variable in time series linear regression
tslm(Life_expectancy ~ Age + Gender + Race + trend, data=ts_df)
Can I do something like this? I actually tried using this as a model and I got a different outcome ...
CommunityBot
- 1
1
vote
1
answer
317
views
how many iterations in breakpoint analysis (bfast)?
I am doing a breakpoint (using bfast) analysis of several Vegetation Index time series (15 years time series; 340 images; MODIS). I have around 20.000 time series ...
CommunityBot
- 1
4
votes
2
answers
41
views
Accounting for non-independence and autocorrelation in HGAM
I am currently trying to fit a HGAM to model differences in daily activity patterns of fish in two treatments. Data were collected with high-resolution telemetry, and I currently have estimates of ...
- 1,011
1
vote
3
answers
680
views
Unsupervised Time series anomaly detection
I have 3D printer that working exactly 400 second for printing element X [0-400].
The printer produce 30 signals (features like VOLT,X,Y,Z,TEMP etc') in frequency of 50HZ (every sample 0.02 ms) ,for ...
CommunityBot
- 1
4
votes
1
answer
142
views
Analysis of proportions over time
My knowledge of statistics is limited and I am looking for resources to read on the matter if possible.
Anyways, I am currently trying to estimate a confidence interval for a proportion over time. ...
- 361
-1
votes
0
answers
8
views
what happens when a network has low closeness centrality - what happens to nodes on the periphery [closed]
I have thirty-nine nodes with closeness centrality scores but I do not know what to say about the nodes on the periphery who do not have scores.
1
vote
1
answer
451
views
Time series analysis: multiplicative model and seasonal adjustment of data
I am trying to help a friend in statistics and this question involving time series came up and I did not know what to do. I tried searching different stack exchange forums for answers, but I believe ...
CommunityBot
- 1
0
votes
0
answers
25
views
AIC from sarima vs arima functions in R
I am doing a report of time series, and while analyzing the time series in R, I noticed the using the sarima function
...
- 69.5k
6
votes
1
answer
793
views
$R^2$ and adjusted $R^2$ in presence of overlapping observations
Given a linear model
$$
y=X\beta+\varepsilon,
$$
the population value of $R^2$ is
$$
R^2=1-\frac{\text{Var}(\varepsilon)}{\text{Var}(y)}.
$$
The vanilla estimator of $R^2$ is
$$
\hat R^2=1-\frac{\...
CommunityBot
- 1
2
votes
3
answers
41
views
Testing forecasting accuracy - outliers [ with example]
I have a simple model that produces forecast values. The model works on hourly data. Now, I am only interested in observations with flags. I would like to identify where the forecasts are ...
- 131k